Features in and around residential gardens affecting the presence and abundance of questing Ixodes ricinus ticks.

People may be exposed to questing Ixodes ricinus ticks in urban settings, e.g. residential gardens. Little is known about the garden characteristics that support a tick population. To determine which features in and around residential gardens support or limit the occurrence and abundance of questing I. ricinus ticks, we sampled them in residential gardens in the Braunschweig region that differed in various intrinsic and extrinsic parameters. We recorded the number of questing nymphal and adult ticks on transects, and by using mixed-effects generalized linear regression models, we related their occurrence and abundance to garden characteristics, meteorological covariates, and landscape features in the vicinity. We detected questing I. ricinus ticks in about 90% of the 103 surveyed gardens. Our occurrence model (marginal R2 = 0.31) predicted the highest probability of questing ticks on transects with hedges or groundcover in gardens, which are located in neighborhoods with large proportions of forest. The abundance of questing ticks was similarly influenced. We conclude that I. ricinus ticks are frequent in residential gardens in Northern Germany and likely associated with intrinsic garden characteristics on a small scale, such as hedges, as well as extrinsic factors on a local scale, such as the proportion of nearby woodland.

Local and landscape environmental heterogeneity drive ant community structure in temperate seminatural upland grasslands.

Environmental heterogeneity is an important driver of ecological communities. Here, we assessed the effects of local and landscape spatial environmental heterogeneity on ant community structure in temperate seminatural upland grasslands of Central Germany. We surveyed 33 grassland sites representing a gradient in elevation and landscape composition. Local environmental heterogeneity was measured in terms of variability of temperature and moisture within and between grasslands sites. Grassland management type (pasture vs. meadows) was additionally included as a local environmental heterogeneity measure. The complexity of habitat types in the surroundings of grassland sites was used as a measure of landscape environmental heterogeneity. As descriptors of ant community structure, we considered species composition in terms of nest density, community evenness, and functional response traits. We found that extensively grazed pastures and within-site heterogeneity in soil moisture at local scale, and a high diversity of land cover types at the landscape scale affected ant species composition by promoting higher nest densities of some species. Ant community evenness was high in wetter grasslands with low within-site variability in soil moisture and surrounded by a less diverse landscape. Fourth-corner models revealed that ant community structure response to environmental heterogeneity was mediated mainly by worker size, colony size, and life history traits related with colony reproduction and foundation. We discuss how within-site local variability in soil moisture and low-intensity grazing promote ant species densities and highlight the role of habitat temperature and humidity affecting community evenness. We hypothesize that a higher diversity of land cover types in a forest-dominated landscape buffers less favorable environmental conditions for ant species establishment and dispersal between grasslands. We conclude that spatial environmental heterogeneity at local and landscape scale plays an important role as deterministic force in filtering ant species and, along with neutral processes (e.g., stochastic colonization), in shaping ant community structure in temperate seminatural upland grasslands.

A database of freshwater macroinvertebrate occurrence records across Cuba.

In light of the ongoing freshwater biodiversity crisis, detailed knowledge regarding the spatial distribution of freshwater species is urgently required, especially in biodiversity hotspots. Here we present a database of georeferenced occurrence records of four freshwater invertebrate taxa groups across Cuba, namely flatworms (Platyhelminthes: Tricladida), insects (Ephemeroptera, Odonata, Hemiptera, Trichoptera, Coleoptera, Diptera), crabs and shrimps (Crustacea: Decapoda), and mollusks (Mollusca). We collated the geographic occurrence information from scientific literature, unpublished field records, museum collections and online databases. The database, comprising 6292 records of 457 species at 1075 unique localities, is organized in 32 fields that contain the information about the taxonomic classification of each recorded species, the sex and life stage of collected individuals; the geographic coordinates, location, author and date of the record and a reference to the original data source. This database provides an important basis towards an improved understanding of the spatial distribution of freshwater biodiversity in Cuba.

Drawing transformation pathways for making use of joint effects of food and energy production with biodiversity agriphotovoltaics and electrified agricultural machinery.

The achievement of the Sustainable Development Goals is being pursued worldwide. While energy production and consumption are to be oriented towards renewable energies, ecologically and socially sustainable agriculture is also a target for science and society. Due to the expansion of renewable energies, agricultural land in particular is the focus of various interest groups, from food production to energy production. In this interdisciplinary study, we show the opportunities and limits of joint synergies from the nexus of food production, energy production, energy consumption, biodiversity protection and social acceptance of renewable energies in a scenario. Biodiversity agriphotovoltaics, i.e. agriphotovoltaics in combination with biodiversity protection measures, such as flower strips, can make a valuable contribution to promoting biotope connectivity in addition to significant energy production. We show this in a GIS-based regional assessment for Lower Saxony in northern Germany. This rough spatial assessment is followed by a modelling of energy production and consumption during the cultivation of a characteristic agricultural field in the loess region of Lower Saxony. Our focus here is on the possibilities of using cable electricity or battery storage for carrying out the cultivation. In an accompanying survey of farmers regarding the use of agriphotovoltaics, we collected and evaluated their prior knowledge, experiences, and attitudes towards this technology. Finally, we show which advantages agriphotovoltaics and electrified agricultural machinery can also have for the sustainable transformation of agriculture and which challenges exist for a truly sustainable use of these technologies.

Impact of the 2020 COVID-19 lockdown on NO2 and PM10 concentrations in Berlin, Germany.

In March 2020, the World Health Organization declared a pandemic due to the rapid and worldwide spread of the SARS-CoV-2 virus. To prevent spread of the infection social contact restrictions were enacted worldwide, which suggest a significant effect on the anthropogenic emission of gaseous and particulate pollutants in urban areas. To account for the influence of meteorological conditions on airborne pollutant concentrations, we used a Random Forest machine learning technique for predicting business as usual (BAU) pollutant concentrations of NO2 and PM10 at five observation sites in the city of Berlin, Germany, during the 2020 COVID-19 lockdown periods. The predictor variables were based on meteorological and traffic data from the period of 2017-2019. The differences between BAU and observed concentrations were used to quantify lockdown-related effects on average pollutant concentrations as well as spatial variation between individual observation sites. The comparison between predicted and observed concentrations documented good overall model performance for different evaluation periods, but better performance for NO2 (R2 = 0.72) than PM10 concentrations (R2 = 0.35). The average decrease of NO2 was 21.9% in the spring lockdown and 22.3% in the winter lockdown in 2020. PM10 concentrations showed a smaller decrease, with an average of 12.8% in the spring as well as the winter lockdown. The model results were found sensitive to depict local variation of pollutant reductions at the different sites that were mainly related to locally varying modifications in traffic intensity.

Water Ecosystem Services Footprint of agricultural production in Central Italy.

The appropriate implementation of the concept of Water-related Ecosystem Services (WES) in water resources planning can support the development of productive activities and, at the same time, sustain local ecosystems. However, such implementation it is only possible when both WES supply and demand are evaluated, eventually with a spatially explicit method, for gaining insights into the ecohydrological behavior of a basin and the anthropogenic pressures on the available water resources. Based on the integration of hydrological modelling and Water Footprint (WF) analysis, this study aims at developing a methodology to analyze both the supply and demand of WES, evaluating a Water Ecosystem Services Footprint (WESF) associated with the agricultural sector. The proposed methodology is based on a 3-tiered approach: 1) evaluating the WES demand determined by the agricultural sector using the WF Assessment methodology; 2) quantifying the WES supply by applying the Soil Water Assessment Tool (SWAT); 3) estimating the green, blue, and gray WESF through dedicated indicators in order to identify the main hotspots. The methodology is applied to a specific case study in the upstream part of the Arno river basin (Central Italy). By means of subnational WF statistics the green, blue, and gray WF of the agricultural sector is calculated, determining the spatial distribution of WES demand in the catchment. SWAT results quantify the available water resources, pointing out the blue/green surface water partitioning, where precipitation is divided into 25% runoff and 46% evapotranspiration, and the associated WES supply. Merging the results, the WESF spatial pattern is evaluated, properly identifying the most critical areas in the catchment. WESF represents an operative tool to look at agricultural water management from an ecosystem-based perspective, supporting the identification of the strategies to explore the sustainable coupling of biosphere and anthroposphere.

Environmental filtering predicts plant-community trait distribution and diversity: Kettle holes as models of meta-community systems.

Meta-communities of habitat islands may be essential to maintain biodiversity in anthropogenic landscapes allowing rescue effects in local habitat patches. To understand the species-assembly mechanisms and dynamics of such ecosystems, it is important to test how local plant-community diversity and composition is affected by spatial isolation and hence by dispersal limitation and local environmental conditions acting as filters for local species sorting.We used a system of 46 small wetlands (kettle holes)-natural small-scale freshwater habitats rarely considered in nature conservation policies-embedded in an intensively managed agricultural matrix in northern Germany. We compared two types of kettle holes with distinct topographies (flat-sloped, ephemeral, frequently plowed kettle holes vs. steep-sloped, more permanent ones) and determined 254 vascular plant species within these ecosystems, as well as plant functional traits and nearest neighbor distances to other kettle holes.Differences in alpha and beta diversity between steep permanent compared with ephemeral flat kettle holes were mainly explained by species sorting and niche processes and mass effect processes in ephemeral flat kettle holes. The plant-community composition as well as the community trait distribution in terms of life span, breeding system, dispersal ability, and longevity of seed banks significantly differed between the two habitat types. Flat ephemeral kettle holes held a higher percentage of non-perennial plants with a more persistent seed bank, less obligate outbreeders and more species with seed dispersal abilities via animal vectors compared with steep-sloped, more permanent kettle holes that had a higher percentage of wind-dispersed species. In the flat kettle holes, plant-species richness was negatively correlated with the degree of isolation, whereas no such pattern was found for the permanent kettle holes.Synthesis: Environment acts as filter shaping plant diversity (alpha and beta) and plant-community trait distribution between steep permanent compared with ephemeral flat kettle holes supporting species sorting and niche mechanisms as expected, but we identified a mass effect in ephemeral kettle holes only. Flat ephemeral kettle holes can be regarded as meta-ecosystems that strongly depend on seed dispersal and recruitment from a seed bank, whereas neighboring permanent kettle holes have a more stable local species diversity.

Novel model coupling approach for resilience analysis of coastal plant communities.

Resilience is a major research focus covering a wide range of topics from biodiversity conservation to ecosystem (service) management. Model simulations can assess the resilience of, for example, plant species, measured as the return time to conditions prior to a disturbance. This requires process-based models (PBM) that implement relevant processes such as regeneration and reproduction and thus successfully reproduce transient dynamics after disturbances. Such models are often complex and thus limited to either short-term or small-scale applications, whereas many research questions require species predictions across larger spatial and temporal scales. We suggest a framework to couple a PBM and a statistical species distribution model (SDM), which transfers the results of a resilience analysis by the PBM to SDM predictions. The resulting hybrid model combines the advantages of both approaches: the convenient applicability of SDMs and the relevant process detail of PBMs in abrupt environmental change situations. First, we simulate dynamic responses of species communities to a disturbance event with a PBM. We aggregate the response behavior in two resilience metrics: return time and amplitude of the response peak. These metrics are then used to complement long-term SDM projections with dynamic short-term responses to disturbance. To illustrate our framework, we investigate the effect of abrupt short-term groundwater level and salinity changes on coastal vegetation at the German Baltic Sea. We found two example species to be largely resilient, and, consequently, modifications of SDM predictions consisted mostly of smoothing out peaks in the occurrence probability that were not confirmed by the PBM. Discrepancies between SDM- and PBM-predicted species responses were caused by community dynamics simulated in the PBM and absent from the SDM. Although demonstrated with boosted regression trees (SDM) and an existing individual-based model, IBC-grass (PBM), our flexible framework can easily be applied to other PBM and SDM types, as well as other definitions of short-term disturbances or long-term trends of environmental change. Thus, our framework allows accounting for biological feedbacks in the response to short- and long-term environmental changes as a major advancement in predictive vegetation modeling.

Reply to the EFSA (2016) on the relevance of recent publications (Hofmann et al. 2014, 2016) on environmental risk assessment and management of Bt-maize events (MON810, Bt11 and 1507).

In this commentary, we respond to a report of the EFSA GMO Panel (EFSA EFSA Supp Publ, 1) that criticises the outcomes of two studies published in this journal (Hofmann et al. Environ Sci Eur 26: 24, 2; Environ Sci Eur 28: 14, 3). Both publications relate to the environmental risk assessment and management of Bt-maize, including maize events MON810, Bt11 and maize 1507. The results of Hofmann et al. (Environ Sci Eur 26: 24, 2), using standardised pollen mass filter deposition measurements, indicated that the EFSA Panel model had underestimated pollen deposition and, hence, exposure of non-target organisms to Bt-maize pollen. The results implied a need for safety buffer distances in the kilometre range for protected nature reserve areas instead of the 20-30 m range recommended by the EFSA Panel. As a result, the EFSA Panel revised their model (EFSA EFSA J 13: 4127, 4), adopting the slope of the empirical data from Hofmann et al. The intercept, however, was substantially reduced to less than 1% at one point by introducing further assumptions based on the estimates of mainly panel members, citing possible 'uncertainty'. Hofmann et al. (Environ Sci Eur 28: 14, 3) published extensive empirical data regarding pollen deposition on leaves. These results were part of a larger 3-year study involving detailed measurements of pollen release, dispersal and deposition over the maize flowering period. The data collected in situ confirmed the previous predictions of Hofmann et al. (Environ Sci Eur 26: 24, 2). Mean levels and observed variability of pollen deposition on maize and four lepidopteran host plants exceeded the assumptions and disagreed with the conclusions of the EFSA Panel. The EFSA Panel reacted in a report (EFSA EFSA Supp Publ, 1) criticising the methods and outcomes of the two published studies of Hofmann et al. while reaffirming their original recommendations. We respond here point-by-point, showing that the critique is not justified. Based on our results on Urtica leaf pollen density, we confirm the need for specific environmental impact assessments for Bt-maize cultivation with respect to protected habitats within isolation buffer distances in the kilometre range.

Correction: Ecosystem Engineering by Plants on Wave-Exposed Intertidal Flats Is Governed by Relationships between Effect and Response Traits.

[This corrects the article DOI: 10.1371/journal.pone.0138086.].

Erratum to: Reply to the EFSA (2016) on the relevance of recent publications (Hofmann et al. 2014, 2016) on environmental risk assessment and management of Bt-maize events (MON810, Bt11 and 1507).

[This corrects the article DOI: 10.1186/s12302-017-0106-0.].

Accumulation and variability of maize pollen deposition on leaves of European Lepidoptera host plants and relation to release rates and deposition determined by standardised technical sampling.

BACKGROUND: Risk assessment for GMOs such as Bt maize requires detailed data concerning pollen deposition onto non-target host-plant leaves. A field study of pollen on lepidopteran host-plant leaves was therefore undertaken in 2009-2012 in Germany. During the maize flowering period, we used in situ microscopy at a spatial resolution adequate to monitor the feeding behaviour of butterfly larvae. The plant-specific pollen deposition data were supplemented with standardised measurements of pollen release rates and deposition obtained by volumetric pollen monitors and passive samplers. RESULTS: In 2010, we made 5377 measurements of maize pollen deposited onto leaves of maize, nettle, goosefoot, sorrel and blackberry. Overall mean leaf deposition during the flowering period ranged from 54 to 478 n/cm2 (grains/cm2) depending on plant species and site, while daily mean leaf deposition values were as high as 2710 n/cm2. Maximum single leaf-deposition values reached up to 103,000 n/cm2, with a 95 % confidence-limit upper boundary of 11,716 n/cm2. CONCLUSIONS: Daily means and variation of single values uncovered by our detailed measurements are considerably higher than previously assumed. The recorded levels are more than a single degree of magnitude larger than actual EU expert risk assessment assumptions. Because variation and total aggregation of deposited pollen on leaves have been previously underestimated, lepidopteran larvae have actually been subjected to higher and more variable exposure. Higher risks to these organisms must consequently be assumed. Our results imply that risk assessments related to the effects of Bt maize exposure under both realistic cultivation conditions and worst-case scenarios must be revised. Under common cultivation conditions, isolation buffer distances in the kilometre range are recommended rather than the 20-30 m distance defined by the EFSA.

Facilitating political decisions using species distribution models to assess restoration measures in heavily modified estuaries.

The European Water Framework Directive requires a good ecological potential for heavily modified water bodies. This standard has not been reached for most large estuaries by 2015. Management plans for estuaries fall short in linking implementations between restoration measures and underlying spatial analyses. The distribution of emergent macrophytes - as an indicator of habitat quality - is here used to assess the ecological potential. Emergent macrophytes are capable of settling on gentle tidal flats where hydrodynamic stress is comparatively low. Analyzing their habitats based on spatial data, we set up species distribution models with 'elevation relative to mean high water', 'mean bank slope', and 'length of bottom friction' from shallow water up to the vegetation belt as key predictors representing hydrodynamic stress. Effects of restoration scenarios on habitats were assessed applying these models. Our findings endorse species distribution models as crucial spatial planning tools for implementing restoration measures in modified estuaries.

Vegetation as self-adaptive coastal protection: Reduction of current velocity and morphologic plasticity of a brackish marsh pioneer.

By reducing current velocity, tidal marsh vegetation can diminish storm surges and storm waves. Conversely, currents often exert high mechanical stresses onto the plants and hence affect vegetation structure and plant characteristics. In our study, we aim at analysing this interaction from both angles. On the one hand, we quantify the reduction of current velocity by Bolboschoenus maritimus, and on the other hand, we identify functional traits of B. maritimus' ramets along environmental gradients. Our results show that tidal marsh vegetation is able to buffer a large proportion of the flow velocity at currents under normal conditions. Cross-shore current velocity decreased with distance from the marsh edge and was reduced by more than 50% after 15 m of vegetation. We were furthermore able to show that plants growing at the marsh edge had a significantly larger diameter than plants from inside the vegetation. We found a positive correlation between plant thickness and cross-shore current which could provide an adaptive value in habitats with high mechanical stress. With the adapted morphology of plants growing at the highly exposed marsh edge, the entire vegetation belt is able to better resist the mechanical stress of high current velocities. This self-adaptive effect thus increases the ability of B. maritimus to grow and persist in the pioneer zone and may hence better contribute to ecosystem-based coastal protection by reducing current velocity.

Ecosystem Engineering by Plants on Wave-Exposed Intertidal Flats Is Governed by Relationships between Effect and Response Traits.

In hydrodynamically stressful environments, some species--known as ecosystem engineers--are able to modify the environment for their own benefit. Little is known however, about the interaction between functional plant traits and ecosystem engineering. We studied the responses of Scirpus tabernaemontani and Scirpus maritimus to wave impact in full-scale flume experiments. Stem density and biomass were used to predict the ecosystem engineering effect of wave attenuation. Also the drag force on plants, their bending angle after wave impact and the stem biomechanical properties were quantified as both responses of stress experienced and effects on ecosystem engineering. We analyzed lignin, cellulose, and silica contents as traits likely effecting stress resistance (avoidance, tolerance). Stem density and biomass were strong predictors for wave attenuation, S. maritimus showing a higher effect than S. tabernaemontani. The drag force and drag force per wet frontal area both differed significantly between the species at shallow water depths (20 cm). At greater depths (35 cm), drag forces and bending angles were significantly higher for S. maritimus than for S. tabernaemontani. However, they do not differ in drag force per wet frontal area due to the larger plant surface of S. maritimus. Stem resistance to breaking and stem flexibility were significantly higher in S. tabernaemontani, having a higher cellulose concentration and a larger cross-section in its basal stem parts. S. maritimus had clearly more lignin and silica contents in the basal stem parts than S. tabernaemontani. We concluded that the effect of biomass seems more relevant for the engineering effect of emergent macrophytes with leaves than species morphology: S. tabernaemontani has avoiding traits with minor effects on wave attenuation; S. maritimus has tolerating traits with larger effects. This implies that ecosystem engineering effects are directly linked with traits affecting species stress resistance and responding to stress experienced.

Spatial stratification of various Lyme disease spirochetes in a Central European site.

To determine whether the genospecies composition of Lyme disease spirochetes is spatially stratified, we collected questing Ixodes ricinus ticks in neighboring plots where rodents, birds, and lizards were present as reservoir host and compared the prevalence of various genospecies. The overall prevalence of spirochetes in questing ticks varied across the study site. Borrelia lusitaniae appeared to infect adult ticks in one plot at the same frequency as did Borrelia afzelii in the other plots. The relative density of questing nymphal and adult ticks varied profoundly. Where lizards were exceedingly abundant, these vertebrates seemed to constitute the dominant host for nymphal ticks, contributing the majority of infected adult ticks. Because lizards support solely B. lusitaniae and appear to exclude other genospecies, their narrow genospecies association results in predominance of B. lusitaniae in sites where lizards are abundant, while limiting its spread to the host's habitat range. To the extent that Central European B. lusitaniae strains are nonpathogenic, the presence of numerous lizards should locally decrease risk of infection for people. Evaluation of regional risk of infection by Lyme disease spirochetes should take the spatial effect of hosts into consideration, which stratify the distribution of specifically infected ticks on a small scale.

Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics.

Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of 'movement ecology'. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide 'mobile links' between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through 'equalizing' and 'stabilizing' mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.

Annual plants under cyclic disturbance regime: better understanding through model aggregation.

In their application for conservation ecology, "classical" analytical models and individual-based simulation models (IBMs) both entail their specific strengths and weaknesses, either in providing a detailed and realistic representation of processes or in regard to a comprehensive model analysis. This well-known dilemma may be resolved by the combination of both approaches when tackling certain problems of conservation ecology. Following this idea, we present the complementary use of both an IBM and a matrix population model in a case study on grassland conservation management. First, we develop a spatially explicit IBM to simulate the long-term response of the annual plant Thlaspi perfoliatum (Brassicaceae), claspleaf pennycress, to different management schemes (annual mowing vs. infrequent rototilling) based on field experiments. In order to complement the simulation results by further analyses, we aggregate the IBM to a spatially nonexplicit deterministic matrix population model. Within the periodic environment created by management regimes, population dynamics are described by periodic products of annual transition matrices. Such periodic matrix products provide a very conclusive framework to study the responses of species to different management return intervals. Thus, using tools of matrix model analysis (e.g., loop analysis), we can both identify dormancy within the age-structured seed bank as the pivotal strategy for persistence under cyclic disturbance regimes and reveal crucial thresholds in some less certain parameters. Results of matrix model analyses are therefore successfully tested by comparing their results to the respective IBM simulations. Their implications for an enhanced scientific basis for management decisions are discussed as well as some general benefits and limitations of the use of aggregating modeling approaches in conservation.

Components of uncertainty in species distribution analysis: a case study of the Great Grey Shrike.

Sophisticated statistical analyses are common in ecological research, particularly in species distribution modeling. The effects of sometimes arbitrary decisions during the modeling procedure on the final outcome are difficult to assess, and to date are largely unexplored. We conducted an analysis quantifying the contribution of uncertainty in each step during the model-building sequence to variation in model validity and climate change projection uncertainty. Our study system was the distribution of the Great Grey Shrike in the German federal state of Saxony. For each of four steps (data quality, collinearity method, model type, and variable selection), we ran three different options in a factorial experiment, leading to 81 different model approaches. Each was subjected to a fivefold cross-validation, measuring area under curve (AUC) to assess model quality. Next, we used three climate change scenarios times three precipitation realizations to project future distributions from each model, yielding 729 projections. Again, we analyzed which step introduced most variability (the four model-building steps plus the two scenario steps) into predicted species prevalences by the year 2050. Predicted prevalences ranged from a factor of 0.2 to a factor of 10 of present prevalence, with the majority of predictions between 1.1 and 4.2 (inter-quartile range). We found that model type and data quality dominated this analysis. In particular, artificial neural networks yielded low cross-validation robustness and gave very conservative climate change predictions. Generalized linear and additive models were very similar in quality and predictions, and superior to neural networks. Variations in scenarios and realizations had very little effect, due to the small spatial extent of the study region and its relatively small range of climatic conditions. We conclude that, for climate projections, model type and data quality were the most influential factors. Since comparison of model types has received good coverage in the ecological literature, effects of data quality should now come under more scrutiny.